Search results for: genomic resilience

Authors: Nguyen J. M., Lucas G., Brunner M., Ruan S., Antonioli D.

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Deep learning based on convolutional neural networks (CNN) is a very powerful technique for classifying information from an image. We propose a new method, DeepNic, to transform each variable of a tabular dataset into an image where each pixel represents a set of conditions that allow the variable to make an error-free prediction. The contrast of each pixel is proportional to its prediction performance and the color of each pixel corresponds to a sub-family of NICs. NICs are probabilities that depend on the number of inputs to each neuron and the range of coefficients of the inputs. Each variable can therefore be expressed as a function of a matrix of 2 vectors corresponding to an image whose pixels express predictive capabilities. Our objective is to transform each variable of tabular data into images into an image that can be analysed by CNNs, unlike other methods which use all the variables to construct an image. We analyse the NIC information of each variable and express it as a function of the number of neurons and the range of coefficients used. The predictive value and the category of the NIC are expressed by the contrast and the color of the pixel. We have developed a pipeline to implement this technology and have successfully applied it to genomic expressions on an Affymetrix chip.

Keywords: tabular data, deep learning, perfect trees, NICS

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Authors: Margarita Santi Becerra Santiago

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The following document addresses the descriptive analysis under the qualitative approach of resilient leadership that allows us to know the importance of the application of a new leadership model to face the new challenges within the gastronomic companies in Mexico. Likewise, to know the main factors that influence resilient leaders and companies to develop new skills to elaborate strategies that contribute to overcoming adversities and managing change. Adversities in a company always exist and challenge us to move and apply our knowledge to be competitive as well as to strengthen our work team through motivation to achieve efficiency and develop in a good organizational climate.

Keywords: challenges, efficiency, leadership, resilience skills

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Authors: Riffat Iqbal, Sidra Ihsan, Andleeb Batool, Maryam Mukhtar

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Glaucoma is a gathering of optic neuropathies described by dynamic degeneration of retinal ganglionic cells. It is clinically and innately heterogenous illness containing a couple of particular forms each with various causes and severities. Primary open-angle glaucoma (POAG) is the most generally perceived kind of glaucoma. This study investigated the genetic association of single nucleotide polymorphisms (SNPs; rs10483727 and rs33912345) at the SIX1/SIX6 locus with primary open-angle glaucoma (POAG) in the Pakistani population. The SIX6 gene plays an important role in ocular development and has been associated with morphology of the optic nerve. A total of 100 patients clinically diagnosed with glaucoma and 100 control individuals of age over 40 were enrolled in the study. Genomic DNA was extracted by organic extraction method. The SNP genotyping was done by (i) PCR based restriction fragment length polymorphism (RFLP) and sequencing method. Significant genetic associations were observed for rs10483727 (risk allele T) and rs33912345 (risk allele C) with POAG. Hence, it was concluded that Six6 gene is genetically associated with pathogenesis of Glaucoma in Pakistan.

Keywords: genotyping, Pakistani population, primary open-angle glaucoma, SIX6 gene

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Authors: Alessandro Balbo, Gianvito Colucci, Matteo Nicoli, Laura Savoldi

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Hydrogen is expected to become a game changer in the energy transition, especially enabling sector coupling possibilities and the decarbonization of hard-to-abate end-uses. The Italian National Recovery and Resilience Plan identifies hydrogen as one of the key elements of the ecologic transition to meet international decarbonization objectives, also including it in several pilot projects for the early development in Italy. This matches the European energy strategy, which aims to make hydrogen a leading energy carrier of the future, setting ambitious goals to be accomplished by 2030. The huge efforts needed to achieve the announced targets require to carefully investigate of their feasibility in terms of economic expenditures and technical aspects. In order to quantitatively assess the hydrogen potential within the Italian context and the feasibility of the planned investments and projects, this work uses the TEMOA-Italy energy system model to study pathways to meet the strict objectives above cited. The possible hydrogen development has been studied both in the supply-side and demand-side of the energy system, also including storage options and distribution chains. The assessment comprehends alternative hydrogen production technologies involved in a competition market, reflecting the several possible investments declined by the Italian National Recovery and Resilience Plan to boost the development and spread of this infrastructure, including the sector coupling potential with natural gas through the currently existing infrastructure and CO2 capture for the production of synfuels. On the other hand, the hydrogen end-uses phase covers a wide range of consumption alternatives, from fuel-cell vehicles, for which both road and non-road transport categories are considered, to steel, and chemical industries uses and cogeneration for residential and commercial buildings. The model includes both high and low TRL technologies in order to provide a consistent outcome for the future decades as it does for the present day, and since it is developed through the use of an open-source code instance and database, transparency and accessibility are fully granted.

Keywords: decarbonization, energy system optimization models, hydrogen, open-source modeling, TEMOA

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Authors: Andrew Hall, Paul Clarkson

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Climate change is predicted to increase the number of extreme weather events intensifying the strain on Railway Earthworks. This paper describes the use of Distributed Rayleigh Sensing to monitor low frequency activity on a vulnerable earthworks sectionprone to landslides alongside a railway line in Northern Spain. The vulnerable slope is instrumented with conventional slope stability sensors allowing an assessment to be conducted of the application of Distributed Rayleigh Sensing as an earthwork condition monitoring tool to enhance the resilience of railway networks.

Keywords: condition monitoring, railway earthworks, distributed rayleigh sensing, climate change

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Authors: Wenqian Bai

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Background: In response to the post-pandemic directives of Xi Jinping concerning the new era of ecological civilization, China has embarked on ecological restoration projects across its territorial spaces. This initiative faces challenges such as complex evaluation metrics and subpar informatization standards. Methodology: This research focuses on Mianzhu City, Sichuan Province, to assess its resource and environmental carrying capacities and the appropriateness of land use for development from ecological, agricultural, and urban perspectives. The study incorporates a range of spatial data to evaluate factors like ecosystem services (including water conservation, soil retention, and biodiversity), ecological vulnerability (addressing issues like soil erosion and desertification), and resilience. Utilizing the Minimum Cumulative Resistance model along with the ‘Three Zones and Three Lines’ strategy, the research maps out ecological corridors and significant ecological networks. These frameworks support the ecological restoration and environmental enhancement of the area. Results: The study identifies critical ecological zones in Mianzhu City's northwestern region, highlighting areas essential for protection and particularly crucial for water conservation. The southeastern region is categorized as a generally protected ecological zone with respective ratings for water conservation functionality and ecosystem resilience. The research also explores the spatial challenges of three ecological functions and underscores the substantial impact of human activities, such as mining and agricultural expansion, on the ecological baseline. The proposed spatial arrangement for ecological restoration, termed ‘One Mountain, One Belt, Four Rivers, Five Zones, and Multiple Corridors’, strategically divides the city into eight major restoration zones, each with specific tasks and projects. Conclusion: With its significant ‘mountain-plain’ geography, Mianzhu City acts as a crucial ecological buffer for the Yangtze River's upper reaches. Future development should focus on enhancing ecological corridors in agriculture and urban areas, controlling soil erosion, and converting farmlands back to forests and grasslands to foster ecosystem rehabilitation.

Keywords: ecological restoration, resource and environmental carrying capacity, land development suitability, ecosystem services, ecological vulnerability, ecological networks

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Authors: Mohammad Ahmad Ahmad Odah

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Aging is a complex biological process characterized by the progressive decline of physiological functions and increased vulnerability to age-related diseases. Epigenetic changes, particularly DNA methylation alterations, play a critical role in the aging process by influencing gene expression and genomic stability. This study explores the potential of epigenetic reprogramming as a strategy to reverse aging phenotypes in human fibroblasts. Using CRISPR-Cas9 gene editing and small molecule inhibitors targeting DNA methylation and histone acetylation, we successfully induced significant changes in DNA methylation and gene expression profiles. Our results demonstrate a global reduction in DNA methylation levels and the identification of differentially methylated regions (DMRs) associated with cellular senescence and DNA repair. Additionally, treated fibroblasts exhibited enhanced proliferative capacity, reduced cellular senescence, and improved differentiation potential. These findings suggest that epigenetic reprogramming could be a promising approach for regenerative medicine, offering potential therapeutic strategies to counteract age-related decline and extend healthy lifespan.

Keywords: epigenetic reprogramming, aging, regenerative medicine, DNA methylation, cellular rejuvenation, CRISPR-Cas9, senescence

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Authors: Hussain-Abdulah Arjmand, Nikki S. Rickard

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The response to stress can be highly heterogenous, and may be influenced by methodological factors. The integrity of data will be optimized by measuring both positive and negative affective responses to an event, by measuring responses in real time as close to the stressful event as possible, and by utilizing data collection methods that do not interfere with naturalistic behaviours. The aim of the current study was to explore short term prototypical responses to major stressor events on outcome measures encompassing both positive and negative indicators of psychological functioning. A novel mobile experience sampling methodology (m-ESM) was utilized to monitor both effective responses to stressors in real time. A smartphone mental health app (‘Moodprism’) which prompts users daily to report both their positive and negative mood, as well as whether any significant event had occurred in the past 24 hours, was developed for this purpose. A sample of 142 participants was recruited as part of the promotion of this app. Participants’ daily reported experience of stressor events, levels of depressive symptoms and positive affect were collected across a 30 day period as they used the app. For each participant, major stressor events were identified on the subjective severity of the event rated by the user. Depression and positive affect ratings were extracted for the three days following the event. Responses to the event were scaled relative to their general reactivity across the remainder of the 30 day period. Participants were first clustered into groups based on initial reactivity and subsequent recovery following a stressor event. This revealed distinct patterns of responding along depressive symptomatology and positive affect. Participants were then grouped based on allocations to clusters in each outcome variable. A highly individualised nature in which participants respond to stressor events, in symptoms of depression and levels of positive affect, was observed. A complete description of the novel profiles identified will be presented at the conference. These findings suggest that real-time measurement of both positive and negative functioning to stressors yields a more complex set of responses than previously observed with retrospective reporting. The use of smartphone technology to measure individualized responding also proved to shed significant insight.

Keywords: depression, experience sampling methodology, positive functioning, resilience

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Authors: Amelia Faotusia

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The blue economy concept was coined by Pacific nations in recognition of the importance of sustainably managing their extensive marine territories. This is especially important for major ocean-based economic sectors of Pacific economies, such as coastal tourism. There is an absence of research, however, on the key ways in which the blue economy concept has emerged in discourse and public policy in Pacific countries, as well as how it articulates with coastal tourism. This research helps to fill such a gap with a specific focus on Tonga through the application of a post-positivist research approach to conduct a desktop study of relevant national documents and qualitative interviews with relevant government staff, civil society organizations, and tourism operators. The findings of the research reflect the importance of institutional integration and partnerships for a successful blue economy transition and are presented in the form of two case studies corresponding to two sub-sectors of Tonga’s coastal tourism sector: (i) the whale-watching and swimming industry, and (ii) beach resorts and restaurants. A thematic analysis applied to the interview data of both cases then enabled the identification of key areas and issues for socio-economic policy intervention and recommendations in support of blue economy transitions in Tonga’s coastal tourism sector. Examples of the relevant areas and issues that emerged included the importance of foreign direct investment, local market access, community-based special management areas, as well as the need to address the anthropogenic impacts of tropical cyclones, whale tourism, plastic litter on coastal assets, and ecosystems. Policy and practical interventions in support of addressing such issues include a proposed restructuring of the whale-watching and swimming licensing system; integration of climate resilience, adaptation, and capacity building as priorities of local blue economy interventions; as well as strengthening of the economic sustainability dimension of blue economy policies. Finally, this research also revealed the need for further specificity and research on the influence and value of local Tongan culture and traditional knowledge, particularly within existing customary marine tenure systems, on Tonga’s national and sectoral blue economy policies and transitions.

Keywords: blue economy, coastal tourism, integrated ocean management, ecosystem resilience

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Authors: Dulanjali Ranasinghe, Isuru Supasan, Kaushalya Premachandra, Ranjan Dissanayake, Ajith Rajapaksha, Eustace Fernando

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Proteomics studies of organisms are considered to be significantly information-rich compared to their genomic counterparts because proteomes of organisms represent the expressed state of all proteins of an organism at a given time. In modern top-down and bottom-up proteomics workflows, the primary analysis methods employed are gel–based methods such as two-dimensional (2D) electrophoresis and mass spectrometry based methods. Machine learning (ML) and artificial intelligence (AI) have been used increasingly in modern biological data analyses. In particular, the fields of genomics, DNA sequencing, and bioinformatics have seen an incremental trend in the usage of ML and AI techniques in recent years. The use of aforesaid techniques in the field of proteomics studies is only beginning to be materialised now. Although there is a wealth of information available in the scientific literature pertaining to proteomics workflows, no comprehensive review addresses various aspects of the combined use of proteomics and machine learning. The objective of this review is to provide a comprehensive outlook on the application of machine learning into the known proteomics workflows in order to extract more meaningful information that could be useful in a plethora of applications such as medicine, agriculture, and biotechnology.

Keywords: proteomics, machine learning, gel-based proteomics, mass spectrometry

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Authors: Andi Aliah Hidayani, Asmi Citra Malina A. R. Tassakka, Andi Parenrengi

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Vanname Shrimp is one of the high yielding varieties that are more resistant to virus attacks. However, now this shrimp more death due to virus attack such as white spot disease caused by white spot syndrome virus (WSSV). Various efforts have done to prevent the disease, like immunostimulatory, probiotics, and vaccine. White spot syndrome virus (WSSV) envelope protein VP19 gene is important because of its involvement in the system infection of shrimp. This study aimed to isolate and characterize an envelope protein VP19 – encoding gene of WSSV using WSSV infected Vanname Shrimp sample from some areas in South Sulawesi (Pangkep, Barru and Pinrang). The genomic of DNA were isolated from shrimp muscle using DTAB-CTAB method. Isolation of gene encoding envelope protein VP19 WSSV ws successfully performed with the results of the length of DNA fragment was 387 bp. The results of homology analysis using BLASTn homology suggested that these isolates genes from Barru, Pangkep and Pinrang have closest relationship with isolates from Mexican.

Keywords: vanname, shrimp, WSSV, viral protein 19

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Authors: Katarzyna Olcoń, Rose M. Pulliam, Dorie J. Gilbert

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This article examines the impact of learning about the history of racial oppression on U.S. university students who participated in a Ghana study abroad which involved visiting the former slave dungeons. Relying on ethnographic observations, individual interviews, and written journals of 27 students (predominantly White and Latino/a and social work majors), we identified four themes: (1) the suffering and resilience of African and African descent people; (2) ‘it’s still happening today’; (3) ‘you don’t learn about that in school’; and (4) remembrance, equity, and healing.

Keywords: racial oppression, anti-racism pedagogy, student learning, social work education, study abroad

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Authors: Nazia Roushan, Maria Kipti

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The sensitive issue of a large-scale entry of Rohingya refugees to Bangladesh has arisen again since August of 2017. Incited by ethnic and religious conflict, the Rohingyas—an ethnic group concentrated in the north-west state of Rakhine in Myanmar—have been fleeing to what is now Bangladesh from as early as the late 1700s in four main exoduses. This long-standing persecution has recently escalated, and accommodating the recent wave of exodus has been especially challenging due to the sheer volume of a million refugees concentrated in refugee camps in two small administrative units (upazilas) in the south-east of the country: the host area. This drastic change in the host area’s social fabric is putting a lot of strain on the country’s economic, demographic and environmental stability, and security. Although Bangladesh’s long-term experience with disaster management has enabled it to respond rapidly to the crisis, the government is failing to cope with this enormous problem and has taken insufficient steps towards improving the living conditions to inhibit the inflow of more refugees. On top of that, the absence of a comprehensive national refugee policy, and the density of the structures of the camps are constricting the upgrading of the shelters to international standards. As of December 2016, the combined number of internally displaced persons (IDPs) due to conflict and violence (stock), and new displacements due to disasters (flow) in Bangladesh had exceeded 1 million. These numbers have increased dramatically in the last few months. Moreover, by 2050, Bangladesh will have as much as 25 million climate refugees just from its coastal districts. To enhance the resilience of the vulnerable, it is crucial to methodically factorize further interventions between Disaster Risk Reduction for Resilience (DRR) and the concept of Building Back Better (BBB) in the rehabilitation-reconstruction period. Considering these points, this paper provides a palette of options for design guidelines related to the living spaces and infrastructures for refugees. This will encourage the development of national standards for refugee camps, and the national and local level rehabilitation-reconstruction practices. Unhygienic living conditions, vulnerability, and the general lack of control over life are pervasive throughout the camps. This paper, therefore, proposes site-specific strategic and physical planning and design for shelters for refugees in Bangladesh that will lead to sustainable living environments through the following: a) site survey of existing two registered and one makeshift unregistered refugee camps to document and study their physical conditions, b) questionnaires and semi-structured focus group discussions carried out among the refugees and stakeholders to understand what the lived experiences and needs are; and c) combining the findings with international minimum standards for shelter and settlement from International Federation of Red Cross and Red Crescent (IFRC), Médecins Sans Frontières (MSF), United Nations High Commissioner for Refugees (UNHCR). These proposals include temporary shelter solutions that balance between lived spaces and regimented, repetitive plans using readily available and cheap materials, erosion control and slope stabilization strategies, and most importantly, coping mechanisms for the refugees to be self-reliant and resilient.

Keywords: architecture, Bangladesh, refugee camp, resilience, Rohingya

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Authors: Sandeep Pandey, Nimra Habib, Ranjana Singh, Abbas Ali Mahdi

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Leukemia is a malignancy of blood that mainly affects children and young adults; while advancement in the early diagnosis will have the potential to improve the outcome of diseases. A wide range of disease including leukemia shows inflammatory signals in their pathogenesis. In a pilot study conducted in our laboratory, 52 people were screened, of which 26 had leukemia and 26 were free from any kind of malignancy. We performed the estimation of the inflammatory cytokine Interleukin-8 and it was found significantly raised in all the leukemia patients concerning healthy volunteers who participated in the study. Flow cytometry had been performed for the confirmation of leukemia and further genomic, and proteomic, analyses of the sample revealed that IL-8 levels showed a positive correlation in patients with leukemia. The results had shown constitutive secretion of interleukin-8 by leukemia cells. So, our finding demonstrated that IL-8 is considered to have a role in the pathogenesis of leukemia, and quantification of IL-8 levels in leukemia conditions might be more useful and feasible in the clinical setting for the prediction of drug responses where it may represent a putative target for innovative diagnostic toward effective therapeutic approaches. However, further research explorations in this area are needed that include a greater number of patients with all different forms of leukemia, and estimating their IL-8 levels may hold the key for the additional predictive values on the recurrence of leukemia and its prognosis.

Keywords: T-ALL, IL-8, leukemia pathogenesis, cancer therapeutics

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Authors: Dipak Subedi, Anil Giri, Christine Whitt, Tia McDonald

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This study aims to understand the impact of the pandemic on the overall economic well-being of the agricultural sector of the United States. The two key metrics used to examine the economic well-being are the bankruptcy rate of the U.S. farm operations and the operating profit margin. One of the primary reasons for farm operations (in the U.S.) to file for bankruptcy is continuous negative profit or a significant decrease in profit. The pandemic caused significant supply and demand shocks in the domestic market. Furthermore, the ongoing trade disruptions, especially with China, also impacted the prices of agricultural commodities. The significantly reduced demand for ethanol and closure of meat processing plants affected both livestock and crop producers. This study uses data from courts to examine the bankruptcy rate over time of U.S. farm operations. Preliminary results suggest there wasn’t an increase in farm operations filing for bankruptcy in 2020. This was most likely because of record high Government payments to producers in 2020. The Federal Government made direct payments of more than $45 billion in 2020. One commonly used economic metric to measure farm profitability is the operating profit margin (OPM). Operating profit margin measures profitability as a share of the total value of production and government payments. The Economic Research Service of the United States Department of Agriculture defines a farm operation to be in a) a high-risk zone if the OPM is less than 10 percent and b) a low-risk zone if the OPM is higher than 25 percent. For this study, OPM was calculated for small, medium, and large-scale farm operations using the data from the Agriculture Resource Management Survey (OPM). Results show that except for small family farms, the share of farms in high-risk zone decreased in 2020 compared to the most recent non-pandemic year, 2019. This was most likely due to higher commodity prices at the end of 2020 and record-high government payments. Further investigation suggests a lower share of smaller farm operations receiving lower average government payments resulting in a large share (over 70 percent) being in the critical zone. This study should be of interest to multiple stakeholders, including policymakers across the globe, as it shows the resilience of the U.S. agricultural system as well as (some) impact of government payments.

Keywords: U.S. farm sector, COVID-19, operating profit margin, farm bankruptcy, ag finance, government payments to the farm sector

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Authors: Olena Mayboroda, Angel Gonzalez Benito, Jonathan Sabate Del Rio, Marketa Svobodova, Sandra Julich, Herbert Tomaso, Ciara K. O'Sullivan, Ioanis Katakis

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DNA amplification is required for most molecular diagnostic applications but conventional PCR has disadvantages for field testing. Isothermal amplification techniques are being developed to respond to this problem. One of them is the Recombinase Polymerase Amplification (RPA) that operates at isothermal conditions without sacrificing specificity and sensitivity in easy-to-use formats. In this work RPA was used for the optical detection of solid-phase amplification of the potential biowarfare agent Yersinia pestis. Thiolated forward primers were immobilized on the surface of maleimide-activated microtitre plates for the quantitative detection of synthetic and genomic DNA, with elongation occurring only in the presence of the specific template DNA and solution phase reverse primers. Quantitative detection was achieved via the use of biotinylated reverse primers and post-amplification addition of streptavidin-HRP conjugate. The overall time of amplification and detection was less than 1 hour at a constant temperature of 37oC. Single-stranded and double-stranded DNA sequences were detected achieving detection limits of 4.04*10-13 M and 3.14*10-16 M, respectively. The system demonstrated high specificity with negligible responses to non-specific targets.

Keywords: recombinase polymerase amplification, Yersinia pestis, solid-phase detection, ELONA

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Authors: Jianli Dong, Fangling Xu, Gengming Huang

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Human endogenous retroviral elements (HERVs) comprise approximately 8% of the human genome. They are thought to be germline-integrated genetic remnants of retroviral infections. Although HERV sequences are highly defective, some, especially the K type (HERV-K), have been shown to be expressed and may have biological activities in the pathogenesis of cancer, chronic inflammation and autoimmune diseases. We found that HERV-K GAG and ENV proteins were strongly expressed in pleomorphic melanoma cells. We also detected a critical role of HERV-K ENV in mediating intercellular fusion and colony formation of melanoma cells. Interestingly, we found that levels of HERV-K GAG and ENV expression correlated with the activation of ERK and loss of p16INK4A in melanoma cells, and inhibition of MEK or CDK4, especially in combination, reduced HERV-K expression in melanoma cells. We also performed a reverse transcription-polymerase chain reaction (RT-PCR) assay using DNase I digestion to remove “contaminating” HERV-K genomic DNA and examined HERV-K RNA expression in plasma samples from HIV-1 infected individuals. We found a covariation between HERV-K RNA expression and CD4 cell counts in HIV-1 positive samples. Although a causal link between HERV-K activation and melanoma development, and between HERV-K activation, HIV-1 infection and CD4 cell count have yet to be determined, existing data support the further research efforts in HERV-K.

Keywords: CD4 cell, HERV-K, HIV-1, melanoma

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Authors: Yutae Lee

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In this paper, we consider the performance and availability of a redundancy model. The redundancy model is a form of resilience that ensures service availability in the event of component failure. This paper considers a 2N redundancy model. In the model there are at most one active service unit and at most one standby service unit. The active one is providing the service while the standby is prepared to take over the active role when the active fails. We design our analysis model using Stochastic Reward Nets, and then evaluate the performance and availability of 2N redundancy model using Stochastic Petri Net Package (SPNP).

Keywords: availability, performance, stochastic reward net, 2N redundancy

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Authors: Johannes Gantner, Michael Held, Matthias Fischer

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The refurbishment of the building stock in terms of energy supply and efficiency is one of the major challenges of the German turnaround in energy policy. As the building sector accounts for 40% of Germany’s total energy demand, additional insulation is key for energy efficient refurbished buildings. Nevertheless the energetic benefits often the environmental and economic performances of insulation materials are questioned. The methods Life Cycle Assessment (LCA) as well as Life Cycle Costing (LCC) can form the standardized basis for answering this doubts and more and more become important for material producers due efforts such as Product Environmental Footprint (PEF) or Environmental Product Declarations (EPD). Due to increasing use of LCA and LCC information for decision support the robustness and resilience of the results become crucial especially for support of decision and policy makers. LCA and LCC results are based on respective models which depend on technical parameters like efficiencies, material and energy demand, product output, etc.. Nevertheless, the influence of parameter uncertainties on lifecycle results are usually not considered or just studied superficially. Anyhow the effect of parameter uncertainties cannot be neglected. Based on the example of an exterior wall the overall lifecycle results are varying by a magnitude of more than three. As a result simple best case worst case analyses used in practice are not sufficient. These analyses allow for a first rude view on the results but are not taking effects into account such as error propagation. Thereby LCA practitioners cannot provide further guidance for decision makers. Probabilistic analyses enable LCA practitioners to gain deeper understanding of the LCA and LCC results and provide a better decision support. Within this study, the environmental and economic impacts of an exterior wall system over its whole lifecycle are illustrated, and the effect of different uncertainty analysis on the interpretation in terms of resilience and robustness are shown. Hereby the approaches of error propagation and Monte Carlo Simulations are applied and combined with statistical methods in order to allow for a deeper understanding and interpretation. All in all this study emphasis the need for a deeper and more detailed probabilistic evaluation based on statistical methods. Just by this, misleading interpretations can be avoided, and the results can be used for resilient and robust decisions.

Keywords: uncertainty, life cycle assessment, life cycle costing, Monte Carlo simulation

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Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

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Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: cancer classification, feature selection, deep learning, genetic algorithm

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Authors: L. K. Davis

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The effects of the evolution force are observable in nature at all structural levels ranging from small molecular systems to conversely enormous biospheric systems. However, the evolution force and work associated with formation of biological structures has yet to be described mathematically or theoretically. In addressing the conundrum, we consider evolution from a unique perspective and in doing so we introduce the “Fundamental Theory of the Evolution Force: FTEF”. We utilized synthetic evolution artificial intelligence (SYN-AI) to identify genomic building blocks and to engineer 14-3-3 ζ docking proteins by transforming gene sequences into time-based DNA codes derived from protein hierarchical structural levels. The aforementioned served as templates for random DNA hybridizations and genetic assembly. The application of hierarchical DNA codes allowed us to fast forward evolution, while dampening the effect of point mutations. Natural selection was performed at each hierarchical structural level and mutations screened using Blosum 80 mutation frequency-based algorithms. Notably, SYN-AI engineered a set of three architecturally conserved docking proteins that retained motion and vibrational dynamics of native Bos taurus 14-3-3 ζ.

Keywords: 14-3-3 docking genes, synthetic protein design, time-based DNA codes, writing DNA code from scratch

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Authors: Fahimeh Palizban, Farshad Noravesh, Amir Hossein Saeidian, Mahya Mehrmohamadi

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In the recent decade, the emergence of liquid biopsy has significantly improved cancer monitoring and detection. Dying cells, including those originating from tumors, shed their DNA into the blood and contribute to a pool of circulating fragments called cell-free DNA. Accordingly, identifying the tissue origin of these DNA fragments from the plasma can result in more accurate and fast disease diagnosis and precise treatment protocols. Open chromatin regions are important epigenetic features of DNA that reflect cell types of origin. Profiling these features by DNase-seq, ATAC-seq, and histone ChIP-seq provides insights into tissue-specific and disease-specific regulatory mechanisms. There have been several studies in the area of cancer liquid biopsy that integrate distinct genomic and epigenomic features for early cancer detection along with tissue of origin detection. However, multimodal analysis requires several types of experiments to cover the genomic and epigenomic aspects of a single sample, which will lead to a huge amount of cost and time. To overcome these limitations, the idea of predicting OCRs from WGS is of particular importance. In this regard, we proposed a computational approach to target the prediction of open chromatin regions as an important epigenetic feature from cell-free DNA whole genome sequence data. To fulfill this objective, local sequencing depth will be fed to our proposed algorithm and the prediction of the most probable open chromatin regions from whole genome sequencing data can be carried out. Our method integrates the signal processing method with sequencing depth data and includes count normalization, Discrete Fourie Transform conversion, graph construction, graph cut optimization by linear programming, and clustering. To validate the proposed method, we compared the output of the clustering (open chromatin region+, open chromatin region-) with previously validated open chromatin regions related to human blood samples of the ATAC-DB database. The percentage of overlap between predicted open chromatin regions and the experimentally validated regions obtained by ATAC-seq in ATAC-DB is greater than 67%, which indicates meaningful prediction. As it is evident, OCRs are mostly located in the transcription start sites (TSS) of the genes. In this regard, we compared the concordance between the predicted OCRs and the human genes TSS regions obtained from refTSS and it showed proper accordance around 52.04% and ~78% with all and the housekeeping genes, respectively. Accurately detecting open chromatin regions from plasma cell-free DNA-seq data is a very challenging computational problem due to the existence of several confounding factors, such as technical and biological variations. Although this approach is in its infancy, there has already been an attempt to apply it, which leads to a tool named OCRDetector with some restrictions like the need for highly depth cfDNA WGS data, prior information about OCRs distribution, and considering multiple features. However, we implemented a graph signal clustering based on a single depth feature in an unsupervised learning manner that resulted in faster performance and decent accuracy. Overall, we tried to investigate the epigenomic pattern of a cell-free DNA sample from a new computational perspective that can be used along with other tools to investigate genetic and epigenetic aspects of a single whole genome sequencing data for efficient liquid biopsy-related analysis.

Keywords: open chromatin regions, cancer, cell-free DNA, epigenomics, graph signal processing, correlation clustering

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Authors: Narin Salehiyan

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The later sequencing of the complete genomes of Mycoplasma genitalium and M. pneumoniae has pulled in significant consideration to the atomic science of mycoplasmas, the littlest self-replicating living beings. It shows up that we are presently much closer to the objective of defining, in atomic terms, the complete apparatus of a self-replicating cell. Comparative genomics based on comparison of the genomic cosmetics of mycoplasmal genomes with those of other microbes, has opened better approaches of looking at the developmental history of the mycoplasmas. There's presently strong hereditary bolster for the speculation that mycoplasmas have advanced as a department of gram-positive microbes by a handle of reductive advancement. Amid this prepare, the mycoplasmas misplaced significant parcels of their ancestors’ chromosomes but held the qualities basic for life. In this way, the mycoplasmal genomes carry a tall rate of preserved qualities, incredibly encouraging quality comment. The critical genome compaction that happened in mycoplasmas was made conceivable by receiving a parasitic mode of life. The supply of supplements from their has clearly empowered mycoplasmas to lose, amid advancement, the qualities for numerous assimilative forms. Amid their advancement and adjustment to a parasitic mode of life, the mycoplasmas have created different hereditary frameworks giving a profoundly plastic set of variable surface proteins to avoid the have safe framework.

Keywords: mycoplasma, plasma, pathogen, genome

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Authors: Mulata Haile Nega, Derebew Fikadu Berhe, Vera Ribeiro Marques

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There is no epidemiologic data on this gene polymorphism in several countries. Therefore, this study aimed to assess the genotype and allele frequencies of the gene variant in three countries. This study involved healthy individuals from Colombia, Mozambique, and Portugal. Genomic DNA was isolated from blood samples using the Qiamp DNA Extraction Kit (Qiagen). The isolated DNA was genotyped using Polymerase Chain Reaction (PCR) - Restriction Fragment Length Polymorphism. Microstat and GraphPad quick cal software were used for the Chi-square test and evaluation of Hardy-Weinberg equilibrium, respectively. A total of 181 individuals’ blood sample was analyzed. Overall, TT (74.0%) genotype was the highest, and CC (7.8%) was the lowest. Country wise genotypic frequencies were Colombia 47(70.2%) TT, 12(17.9%) TC and 8(11.9%) CC; Mozambique 47(88.7%) TT, 5(9.4%) TC, and 1(1.9%) CC; and Portugal 40(65.6%) TT, 16(26.2%) TC, and 5(8.2%) CC. The reference (T) allele was highest among Mozambicans (93.4%) compared to Colombians (79.1%) and Portuguese (78.7%). Mozambicans showed statistically significant genotypic and allelic frequency differences compared to Colombians (p<0.01) and Portuguese (p <0.01). Overall and country-wise, the CC genotype was less frequent and relatively high for Colombians and Portuguese populations. This finding may imply statins risk-benefit variability associated with CC genotype among these populations that needs further understanding.

Keywords: c.521T>C, polymorphism, SLCO1B1, SNP, statins

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Authors: Ruchi Agarwal, Jake Ansell

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Austerity impacts on all aspects of society. Companies into the future will have to be more capable of dealing with the risks they face. Enterprise Risk Management (ERM) has widely been accepted in recent years as an approach to manage risks within businesses. ERM attempts to tackle risk holistically with gains from opportunities in a managing risk and reduction in the risk of failure. The paper reviews merits and demerits of approaches to risk management in regard to antifragility. A qualitative study has investigated current practices and the problems with ERM implementation by interviewing over 25 chief risk officers and senior management. The findings indicate the gap in ERM description, understanding, and implementation. The paper suggests risk learning and expertise knowledge supports development of effective enterprise risk management by designing systems with inherent resilience.

Keywords: risk management, interviews, antifragility, failure

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Authors: Yee Hui Lim, Elena Gusareva, Irvan Luhung, Yulia Frank, Stephan Christoph Schuster

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Environmental pollution from microplastics (MPs) is an emerging concern worldwide. While the presence of microplastics has been well established in the marine and terrestrial environments, the prevalence of microplastics in the atmosphere is still poorly understood. Wet depositions such as rain or snow scavenge impurities from the atmosphere as it falls to the ground. These wet depositions serve as a useful tool in the removal of airborne particles that are suspended in the air. Therefore, the aim of this study is to investigate the presence of atmospheric microplastics and fibres through the analysis of air, rainwater and snow samples. Air samples were collected with filter-based air samplers from outdoor locations in Singapore. The sampling campaigns were conducted during and after each rain event. Rainwater samples from Singapore and Siberia were collected as well. Snow samples were also collected from Siberia as part of the ongoing study. Genomic DNA was then extracted from the samples and sequenced with shotgun metagenomics approach. qPCR analysis was conducted to quantify the total bacteria and fungi in the air, rainwater and snow samples. The results compared the bioaerosol profiles of all the samples. To observe the presence of microplastics, scanning electron microscope (SEM) was used. From the preliminary results, microplastics were detected. It can be concluded that there is a significant amount of atmospheric microplastics present, and its occurrence should be investigated in greater detail.

Keywords: atmospheric microplastics, metagenomics, scanning electron microscope, wet deposition

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Authors: Lamis Naddaf, Yuval Tabach

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In this research, we identified the missense genetic variants that have the potential to enhance resistance against cancer. Such field has not been widely explored, as researchers tend to investigate mutations that cause diseases, in response to the suffering of patients, rather than those mutations that protect from them. In conjunction with the genomic revolution, and the advances in genetic engineering and synthetic biology, identifying the protective variants will increase the power of genotype-phenotype predictions and can have significant implications on improved risk estimation, diagnostics, prognosis and even for personalized therapy and drug discovery. To approach our goal, we systematically investigated the sites of the coding genomes and picked up the alleles that showed a correlation with the species’ cancer resistance. We predicted 250 protecting variants (PVs) with a 0.01 false discovery rate and more than 20 thousand PVs with a 0.25 false discovery rate. Cancer resistance in Mammals and reptiles was significantly predicted by the number of PVs a species has. Moreover, Genes enriched with the protecting variants are enriched in pathways relevant to tumor suppression like pathways of Hedgehog signaling and silencing, which its improper activation is associated with the most common form of cancer malignancy. We also showed that the PVs are more abundant in healthy people compared to cancer patients within different human races.

Keywords: comparative genomics, machine learning, cancer resistance, cancer-protecting alleles

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Authors: Marzieh Jafarzadeh, Fatemeh Rezaee

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Introduction: The effect of ionizing radiation on human health can be effective for genomic integrity and cell viability. It also increases the risk of cancer and malignancy. Therefore, X-ray behavior and absorption dose calculation are considered. One of the applicable tools for calculating and evaluating the absorption dose in human tissues is Monte Carlo simulation. Monte Carlo offers a straightforward way to simulate and integrate, and because it is simple and straightforward, Monte Carlo is easy to use. The Monte Carlo BEAMnrc code is one of the most common diagnostic X-ray simulation codes used in this study. Method: In one of the understudy hospitals, a certain number of CT scan images of patients who had previously been imaged were extracted from the hospital database. BEAMnrc software was used for simulation. The simulation of the head of the device with the energy of 0.09 MeV with 500 million particles was performed, and the output data obtained from the simulation was applied for phantom construction using CT CREATE software. The percentage of depth dose (PDD) was calculated using STATE DOSE was then compared with international standard values. Results and Discussion: The ratio of surface dose to depth dose (D/Ds) in the measured energy was estimated to be about 4% to 8% for bone and 3% to 7% for bone marrow. Conclusion: MC simulation is an efficient and accurate method for simulating bone marrow and calculating the absorbed dose.

Keywords: Monte Carlo, absorption dose, BEAMnrc, bone marrow

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Authors: Badrane Hasnaa, Bouzahir Brahim

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This article examines the impact of fintech technologies on crowdfunding, particularly their potential to enhance financial inclusion and promote responsible finance. It explores how the adoption of blockchain, artificial intelligence, and other fintech innovations is transforming crowdfunding by making it more accessible, transparent, and ethical. By analyzing case studies and recent data, the article illustrates how these technologies help overcome traditional barriers to financing while promoting sustainable financial practices. The findings suggest that integrating fintech into crowdfunding can not only broaden access to funding for marginalized populations but also encourage more responsible management of financial resources, contributing to a fairer and more resilient economy.

Keywords: crowdfunding, fintech, inclusion financière, finance responsible, blockchain, resilience financière

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Authors: Anna Bak-Klimek, Emily Spencer, Siew Lee, Karen Campbell, Wendy McInally

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Background & Significance: Over half of Teenagers and Young Adults (TYAs) say that they experience psychological distress after cancer diagnosis and TYAs with cancer are at higher risk of developing distress compared to other age groups. Despite this there are no age-appropriate interventions to help TYAs manage distress and there is a lack of conceptual understanding of what causes distress in this population group. This makes it difficult to design a targeted, developmentally appropriate intervention. This review aims to identify the key determinants of distress in TYAs affected by cancer and to propose an integrative model of cancer-related distress for TYAs. Method: A literature search was performed in Cochrane Database of Systematic Reviews, MEDLINE, PsycINFO, CINAHL, EMBASE and PsycArticles in May-June, 2022. Quantitative literature was systematically reviewed on the relationship between psychological distress experienced by TYAs affected by cancer and a wide range of factors i.e. individual (demographic, psychological, developmental, and clinical factors) and contextual (social/environmental) factors. Evidence was synthesized and correlates were categorized using the Biopsychosocial Model. The full protocol is available from PROSPERO (CRD42022322069) Results: Thirty eligible quantitative studies met criteria for the review. A total of twenty-six studies were cross-sectional, three were longitudinal and one study was a case control study. The evidence on the relationship between the socio-demographic, illness and treatment-related factors and psychological distress is inconsistent and unclear. There is however consistent evidence on the link between psychological factors and psychological distress. For instance, the use of cognitive and defence coping, negative meta-cognitive beliefs, less optimism, a lack of sense of meaning and lower resilience levels were significantly associated with higher psychological distress. Furthermore, developmental factors such as poor self-image, identity issues and perceived conflict were strongly associated with higher distress levels. Conclusions: The current review suggests that psychological and developmental factors such as ineffective coping strategies, poor self-image and identity issues may play a key role in the development of psychological distress in TYAs affected by cancer. The review proposes a Positive Developmental Psychology Model of Distress for Teenagers and Young Adults affected by cancer. The review highlights that implementation of psychological interventions that foster optimism, improve resilience and address self-image may result in reduced distress in TYA’s with cancer.

Keywords: cancer, determinant, psychological distress, teenager and young adult, theoretical model

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